Abstract Poor adherence to self-care guidelines among adults with cystic fibrosis (CF) reduces quality of life, accelerates lung function decline, increases rate of pulmonary exacerbations and hospitalizations, and leads to earlier death. Prior research has shown that poor adherence for adults with CF includes: the high burden of care linked to daily treatment regimen; health beliefs about treatment efficacy; and poor mental health. Further, pilot data from our study at Northwell Health showed poor adherence to be associated with lack of access to medications and devices, and lack of skills needed to correctly perform the treatments. We also found that social isolation among CF adults may be further exacerbating depression, anxiety and adherence. While these factors are each associated with poor adherence in general, not all of them may be relevant for each particular patient. Studies in other chronic disease populations have determined that the wider social contexts of patients, particularly the members of their social networks, can impact adherence in various ways. Although it is known that a person's social environment influences health decisions, we do not yet understand what specific components of a person's social network influence adherence to treatment recommendations for CF adults. The proposed exploratory study will use methods from qualitative research and social network analysis (SNA) to define influential components of social networks impacting adherence. Our conceptual model will be the Network Episode Model (NEM) which sees health and illness behaviors as embedded in social processes that create an illness career or trajectory. This model emphasizes the importance of health discussion networks, and the multiple and dynamic pathways that individuals and their social networks follow in response to the onset of an illness. We will recruit 30 CF adults to participate in the study and administer closed ended surveys covering: socio- economic status, health, and adherence. Adherence will also be tracked using prescription refill history. SNA- based name generating questionnaires and the validated McGill Illness Narrative Interview modified for CF adherence will be administered to map participants' social networks. We will then undertake thematic analysis of the qualitative data and conduct statistical analysis of quantitative data using social network analysis to look for associations between adherence and other variables. Our goal is build a preliminary social network based statistical model for CF adherence that can be tested over multiple time-points among a much larger sample size in a future study, and which may be applicable to other adherence for other chronic lung diseases (asthma, COPD). This work fulfills AHRQ's mission to improve health care quality outcomes by providing integrated coordinated whole-person 360-degree care. It seeks to do this using social network analysis to understand the wider social-contextual factors leading to poor adherence among adults with CF. The study is innovative as it will be the first to apply SNA to CF adherence toward a preliminary mathematical model for adult CF adherence.